248. Better Together: How to Supercharge Your Team’s Productivity
The secret to effective teamwork and collaboration.
To collaborate, we have to communicate. As Molly Sands knows, “The more that we can get on the same page, the more effective we are.”
Sands is a behavioral scientist and the head of the Teamwork Lab at Atlassian, where she researches how teams can collaborate more effectively and efficiently, especially in distributed and hybrid work environments. As she’s seen in her research and within her own team, “People can accomplish a lot more together when they work well together.” The key to unlocking that potential lies in communication that aligns people not just in their activity, but in their deeper goals and vision. “The best work happens when you start by asking why,” she says, “getting people to really understand: why is this a problem, why do we wanna solve it, and how are we uniquely positioned to do that? The more that we can map this out together, the more effective our teams tend to be.”
In this episode of Think Fast, Talk Smart, Sands and host Matt Abrahams discuss strategies for effective collaboration, from “page-led” meetings and asynchronous video messages to using AI as a collaborator. Whether your team is working face-to-face or across time zones, Sands’ insights show how better communication is the key to better collaboration.
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00:00 - Introduction
02:32 - How the Teamwork Lab Works
04:03 - Top Challenges for Teams
04:37 - Clarifying Goals & Alignment
07:19 - AI as a Collaborative Partner
09:25 - Atlassian’s AI Onboarding Buddy
12:49 - Rethinking Meetings
15:58 - Three Types of Work Time
17:17 - Replacing Meetings with Asynchronous Video
20:02 - The Final Three Questions
24:11 - Conclusion
[00:00:00] Matt Abrahams: Collaboration is critical to teaming, but how do we do it so that we feel effective and unburdened? My name is Matt Abrahams and I teach strategic communication at Stanford Graduate School of Business. Welcome to Think Fast Talk Smart, the podcast. Today I look forward to chatting with Molly Sands. Molly is a behavioral scientist and the head of the Teamwork Lab at Atlassian. She and her team conduct research into best practices for high performing teams. Her work focuses on understanding how teams can collaborate more effectively in a distributed and hybrid work environment, especially in the world of AI. Welcome Molly. I have long admired the work of your team and I'm really excited to have a conversation about the work you do.
[00:00:46] Molly Sands: Thank you so much. I'm excited to be here.
[00:00:48] Matt Abrahams: Okay, shall we get started?
[00:00:49] Molly Sands: Let's do it.
[00:00:50] Matt Abrahams: Awesome. So the Teamwork Lab studies many aspects of teaming and productivity. How do you determine what to study and do you have some guiding principles for the work that you do?
[00:01:00] Molly Sands: I am really focused on a few things in our work. We have a couple key beliefs about teamwork, and one is that people can accomplish a lot more together when they work well together. And the other is that in most companies today, it is way too hard to work together. And the more that we can get on the same page about what we're trying to achieve together and how we're going to get there, the more effective we are. Those are sort of my guiding philosophies around how do teams work effectively together, and we anchor our research in a couple areas. So one, my team, the Teamwork Lab at Atlassian, we study teams across the world.
[00:01:42] So we will survey thousands of teams. We'll talk to leaders. We'll do lots of different types of research, and then we also study teams within the company. And within Atlassian, we're really able to get in the mix with teams and change how they work and measure lots of different types of outcomes. And so from those two approaches, we get a really good sense of what are the challenges that most people are facing today and that all of our customers really care about and need us to come up with better solutions for. And then we also have this amazing experimental pool, and so we can start to really change ways of working and then see how that impacts outcomes.
[00:02:21] Matt Abrahams: In that research that you do, at least trying to identify what the big challenges, are there two or three that stand out in terms of what really teams struggle with?
[00:02:29] Molly Sands: Yeah, so, goals. What actually matters is huge for teams and how people invest their time in companies today. And so we'd spend a lot of time studying and thinking about how do we get clear on what we're trying to do and how do we invest our times in ways that are actually meaningful and help us do real work and not just talk about work.
[00:02:55] Matt Abrahams: Do you have suggestions for how people can help identify their goals? And then I know something you spend a lot of time on is alignment, getting people aligned to those goals. 'Cause I've been in several organizations where I thought we were working in one direction and it turns out others thought we were working in another. So how do we determine what those goals are and how do we get alignment towards them?
[00:03:13] Molly Sands: So I think a lot of the best work happens when you start by asking why, right? And you are really focused on what are we, what do we want the true outcome to look like? And in a lot of companies and a lot of teams today, people get activities confused with outcomes, right? It's less about what is the business problem we're solving, what is the customer problem we're solving, and more about what activities are we doing to get there? And so getting really clear about the problems is really the first step to having a great strategy and then being more explicit about how are we going to get there, and getting that input, getting people to really understand why is this a problem? Why do we wanna solve it? And how are we uniquely positioned to do that? All of that product thinking, is really how I think about it, tends to help teams get much better aligned. And then being explicit, right? There's so many moments, you just referenced times of thinking, well, I thought we were all on the same page, but I never said it out loud. And your colleagues and your teammates are not mind readers. So the more that we can really map this out together, the more effective our teams tend to be.
[00:04:27] Matt Abrahams: I think taking the time to really reflect on what is important here, what's the problem we're solving, why are we doing this, and then making it explicit by documenting it and communicating it, are really important. And I have found in the practice that I do, and when I go into organizations, having people just share what is the goal and have everybody give their version of it. People are often very surprised that they weren't aligned. So explicitly not just providing it, but making sure people share their take on it can be really helpful too.
[00:04:56] Molly Sands: Yeah. I always tell managers or anyone that's leading a project, one of the first things you should do is ask everyone to tell you what they think you're trying to accomplish.
[00:05:06] Matt Abrahams: And a powerful question I found, I'd be curious to get your input on it, is asking people, what does success look like? What does success of this team look like?
[00:05:13] Molly Sands: We actually start every project we do in our platform, we have a way that people can document this, but what are we doing? Why are we doing it? And what does success look like? And just by asking those three questions, and writing something up that everyone working on that project reads and thinks about and gives feedback on, that is such a fast way to actually accelerate everything that happens from that point on.
[00:05:37] Matt Abrahams: Yeah, what are we doing? Why is it important? And what does success look like? Really important questions. I think another important question, and I'm sure this won't surprise you, is I'd love to talk about AI and AI's role. It's certainly affecting work, period, but also in teams. Your research shows a shift towards using AI as a collaborator. Can you help us understand what that looks like? What recommendations do you have to leverage AI to help teams be more successful?
[00:06:01] Molly Sands: One of the things we saw earliest as AI was really taking hold of how we do work was that people's mindset around it mattered in a huge way. And so if you really think of AI as a collaborator, rather than just a doer, but you're actually thinking about AI more like a teammate and someone that can push your thinking forward and that you can go back and forth with. Those are the people that are seeing much better outcomes, and that's across a lot of things. So they're seeing more efficiency in the work they're doing. They're able to do tasks faster, but those folks are also seeing better quality work and their teams are viewing them as more innovative. And some of the promise of AI that we're all excited about is really coming true for the people that start to think about AI in that collaborative mindset, rather than simply as, oh, well, I can delegate and automate a few things.
[00:06:58] Matt Abrahams: Can you give us a few examples of what true collaboration with AI might look like? Does it have a seat at the table? Is it in the Zoom meeting with me? Am I asking it questions like a colleague? What does that look like?
[00:07:09] Molly Sands: So I think it is great to think of AI as a quick way to get some information that you need, but it's also about that back and forth interaction. So actually creating things, and not just taking the first output that you get, but actually going back and forth, debating, asking questions, having AI push your thinking and pushing back too, saying, I don't think this is right. I know about this other thing. How do we incorporate this? And much in the way you would go about collaborating with other people where it is a back and forth.
[00:07:43] Matt Abrahams: We had a really insightful episode we did with Jeremy Utley, where we talked about how treating AI as a conversation partner, not just as a search engine, really can change the dynamic. And it sounds like that's what you're advocating for is really engage in dialogue, talk to it, and challenge it, and it will help you benefit. Can you give us an example of using AI as a tool to help you? I read about, or listened to an episode of something where Atlassian has built an onboarding tool out of AI to help people get started and be more productive.
[00:08:12] Molly Sands: Yeah, we've had great success with onboarding with an AI buddy. So we built what we call, her name is NORA Atlassian onboarding Rovo agent. And NORA has access to all of the data that we have about policies and people programs and how we run our company, how people get set up in our systems. And when our new hires join, they have a variety of touchpoints with other humans, but we also give them access to NORA and say, Hey, if you have any of those basic HR questions, ask her. If you have any questions about how things operate in this company, if you're wondering who to ask about this, if you don't know how to file a ticket.
[00:08:58] Just all of those logistical things that come up as you're joining. And you don't really wanna go to your brand new manager and be like, oh, I have this like really annoying list of twenty-five questions about logistical things. You wanna be showing up as strategic in those conversations, and NORA is your buddy for everything that you need, and people feel a lot more comfortable asking questions. They don't worry about how AI is going to perceive those questions, so they really ask everything they want. And we've also found that this has vastly increased how much people use AI as a collaborator, as they onboard into their new role.
[00:09:37] Matt Abrahams: So it's an on-ramp to helping them feel comfortable using AI as a tool to help them with their work. I like that.
[00:09:42] Molly Sands: Yeah. And so we've seen a really strong relationship there that just this initial touch point sets that expectation that this is a way that we work in this company and this is how you're going to get information.
[00:09:54] Matt Abrahams: I know when I would onboard on companies, I would always feel so embarrassed 'cause I couldn't remember something I was taught and I'd have to go back and ask. And I feel like I'm trying to set a good impression and now everybody thinks I can't remember anything. To have a tool like that would be helpful. So finding niche needs and building AI tools to help, not only help with whatever that need was, but it also helps people feel more comfortable using AI as a collaborator.
[00:10:16] Molly Sands: Yeah, and I think it's important for companies to think about where they have really robust knowledge. So AI works the best when it has access to the right information, and so in HR policies tend to be really carefully documented. You actually do need to have good resources for any new employee about what your benefits look like, about how people manage different systems, about how they integrate into teams. We're able to pretty easily create customized onboarding plans using AI as well. And so when all that information is available, you can easily build on top of it. And so I usually encourage leaders to think about where are pockets within your company that you have that great data already there, and to think about those as use cases where you can get some clear ones.
[00:11:07] Matt Abrahams: Yeah, clear, easy pilot wins and really get that momentum going. I appreciate that a lot. As you and I talked about before we came on the air, meetings can be really useful for teaming, but many of us struggle with the meetings we have. We feel like they're too many. We feel like we're victimized by poor meetings. They zap our time. I know you have done research into meetings and actually at Atlassian, you guys have some really interesting approaches. I know you use Loom videos for asynchronous updates. You have what are called page led meetings. Can you define these two approaches because I think they're really unique and could be helpful for many. And then what other advice do you have generally in terms of how we meet better, when we meet better, who we meet with. So I'd love to get specific on what you all have done, because I think it transfers to many people, and I just love generally what your research has found.
[00:11:53] Molly Sands: Meetings are one of the biggest challenges in people's jobs, right? Anytime that we run research about what's holding people back from achieving what they want to at work, meetings are the number one thing. It's the biggest barrier to productivity, but it's essential that we talk to each other. That's how we come up with great ideas. That's how we create together. There are so many things that are so important about that. And in the last few years, as companies have embraced much more distributed global work, people have brought a lot of the meeting habits, that we did not love in the office, online with them. And so now we're all stuck in these back to back meetings all day long.
[00:12:31] And what we really think about is taking control of our time and solving the problems that meetings are supposed to solve in different, more efficient and more effective ways. And so I think people should think about having kind of three types of time in their day. One is time for deep work. You really do need time to think, to write, to create, depending on what your job is, that time will look different, but the time where you're using your brain in the most powerful ways, and now you've got AI as a partner during that time as well. And then we should have meetings. And at Atlassian we do page led meetings, and we've done a lot of research on this idea, and the basic idea is that you put together a really clear synopsis of what everyone needs to know as context to have a conversation.
[00:13:21] This works really well when you're trying to make a decision, when you're trying to align people, when you want feedback on a perspective or path forward. So any of those kinds of meetings where you really are bringing a group together to say, let's chart the path forward or make sure everyone's at least aware of it. Those moments work really great for this page led meeting concept. And the pages should be short. Pages should be no more than a five minute read. You don't want people reading for hours together.
[00:13:51] Matt Abrahams: And do people read those when they all convene together, is the expectation that you read them in advance? Because I know Amazon does in the room, we all read.
[00:13:58] Molly Sands: Yes, we do in the room as well. The pre-reads are tough. People don't do them. You're not sure if people did them. You maybe did it, but it was four days ago and now that's not top of mind for you. So it's a great way at the beginning to just set the context for everyone and we ask people to comment.
[00:14:16] Matt Abrahams: So you said there were three ways of using time. I'd love to revisit those. And then, I hate update meetings and I know you all have an interesting way of getting that information that I think everybody should consider.
[00:14:26] Molly Sands: Yes. Okay. So three ways of using time. One is traditional meetings, another is deep work, and the third is, and this sounds so silly, but collaboration, more fluid collaboration. And what we've seen in people trying to fix meetings is that some teams have shifted to way too much structure. And so every time that you're bringing people together to talk, it is like very agenda led and someone is giving a presentation and that's not the moment where you can really create together. And so, especially if you're working on distributed teams where people are in lots of different locations, having these more fluid moments where you can come together and really just work. That could be pair programming, that could be writing a page together, that could be doing a creative brief or coming up with concepts, brainstorming. All these different ways that we really do work together, and I think people need to start to think about that as a category that is different from a formal structured meeting, but make a lot more time for that kind of collaborative work.
[00:15:35] Matt Abrahams: So it's this notion of deep time where you're by yourself, maybe with an AI collaborator, working on something. It's the typical, traditional, structured meeting led with pages where you all sync up on what it is we're talking about, and then the more collaborative ideative time where people come together and can really have the freedom to do the work that needs to be done.
[00:15:56] Molly Sands: Exactly. And in order to have time to do all of those things, you cannot be in back to back standing meetings where you were giving status updates. And people don't have meetings for no reason, even if they're not effective, which most of the time they tell us they are not. They're trying to solve a problem and usually that problem is getting or sharing information. And so we do a lot of asynchronous video. We have a tool called Loom that we use, which lets you record yourself talking. You can screen record, you can just record a video of you, and that captures a lot more signal than simply a written update. We find that people feel more connected to other people when they communicate through video, and that there's a lot of benefits to giving more of that personal touch to information.
[00:16:45] And so we ask people to usually do their updates or status updates, either through writing or through Loom videos, depending on how much context they need to share. And we align all of our work to goals. So there's a whole system and infrastructure around goals. What are teams working on? Where do you have shared goals? And this creates a lot of that clarity that we were talking about in the beginning, right, of what are we trying to achieve together. And just repeatedly having people look at and remind themselves of that information through our ways of sharing updates is huge for staying on the same page about what we're really trying to achieve.
[00:17:25] Matt Abrahams: I really like that idea of recording the update. Not only do you get more information, as you said, more signal, but people can take in that information when they need it. So I will often coach people in the organizations I go into where people are just so frustrated with these long update meetings where maybe ten percent is useful to you. Have everybody record their sessions in a structured way, so you know, you're getting the same type of information and the requirement is that you just watch it in advance of the meeting. So when you come together, you can actually have a discussion about what you learned rather than wasting the time of hearing everybody's update. And I really like that. And I also like what you said about tying these into the broader goal and always reminding people how these things connect. So I think those are very useful tools to help people be more efficient and effective in their meetings. So the idea is not get rid of all the meetings. The idea is maximize the utility of the meetings for what they're meant for. So thank you for that.
[00:18:20] So Molly, before we end, I like to ask everybody three questions. One I make up just for you and two, I've been asking everybody for as long as this podcast has gone on. Are you up for that?
[00:18:29] Molly Sands: I'm up for that.
[00:18:30] Matt Abrahams: I am curious, what is something that your team is currently studying or working on that has you really excited?
[00:18:36] Molly Sands: We are working on a lot of research about how you really make AI part of the team. So we see people are using AI more and more at work and in their personal lives, but how do we solve team level challenges and problems, the things that are really hard about working together. And so we are doing some really interesting interventions right now with teams where we embed AI not just as an individual collaborator for everyone on the team, but also into some of these team processes and ways of working. And I'm very excited to see more of what we learned from that.
[00:19:13] Matt Abrahams: I would love for you when you start getting results to have you share some of that, and we will try to get that information out because I see that as a big unlock, but I also see it as something that could be a real challenge. So it'd be really interesting to find what you've learned. Question number two. Who is a communicator that you admire and why?
[00:19:29] Molly Sands: I really admire Molly Graham. She, I think, is a fantastic communicator in really synthesizing some of the core things that are hard about work and putting analogies behind them that make them very memorable. And I've been really impressed with her work. She's most well known for the giveaway your Legos piece that she's written about how to scale in companies and how to grow. But I think all of her content is so actionable and memorable.
[00:20:01] Matt Abrahams: So I like that it's actionable. That's what we're all about is practical and tactical actions. But it sounds like the ability to synthesize and to make things accessible through things like analogies, which are wonderful skills for anybody hoping to be a good communicator. Final question, what are the first three ingredients that go into a successful communication recipe?
[00:20:21] Molly Sands: Making it resonant. You want people to immediately feel what you're talking about. Clarity. And I think passion, when you care about the topic, when you care about what your message is, that really comes through in the way you communicate.
[00:20:40] Matt Abrahams: Making it resonant, relevant, salient, really important. Being clear. You've talked about clarity a lot today. Clarity of goal, alignment to goal, clarity of messages. And then passion. And you clearly are passionate about helping people collaborate and work better in teams. Thank you for the best practices. Thank you for helping us understand the details of what goes into collaboration and effective work, and thank you for your time and helping all of us be better in our teaming.
[00:21:06] Molly Sands: Yeah. Thank you so much for having me and for this wonderful discussion.
[00:21:12] Matt Abrahams: Thank you for joining us for another episode of Think Fast Talk Smart, the podcast. To learn more about teams and teaming, please listen to episode 242 with Colin Fisher. This episode was produced by Katherine Reed, Ryan Campos, and me, Matt Abrahams. Our music is from Floyd Wonder. With special thanks to the Podium Podcast Company. Please find us on YouTube and wherever you get your podcasts. Be sure to subscribe and rate us. Also follow us on LinkedIn, TikTok, and Instagram. And check out fastersmarter.io for deep dive videos, English language learning content, and our newsletter. Please consider our premium offering for extended Deep Thinks episodes, AMAs, Ask Matt Anythings, and much more at fastersmarter.io/premium.